Service Scheduling Based on Edge Computing for Power Distribution IoT

With the growing amounts of multi-micro grids,electric vehicles,smart home,smart cities connected to the Power Distribution Internet of Things(PD-IoT)system,greater computing resource and communication bandwidth are required for power distribution.It probably leads to extreme service delay and data congestion when a large number of data and business occur in emergence.This paper presents a service scheduling method based on edge computing to balance the business load of PD-IoT.The architecture,components and functional requirements of the PD-IoT with edge computing platform are proposed.Then,the structure of the service scheduling system is presented.Further,a novel load balancing strategy and ant colony algorithm are investigated in the service scheduling method.The validity of the method is evaluated by simulation tests.Results indicate that the mean load balancing ratio is reduced by 99.16%and the optimized offloading links can be acquired within 1.8 iterations.Computing load of the nodes in edge computing platform can be effectively balanced through the service scheduling.

ELECTRO-HYDRAULIC COMPOUND CONTROL METHOD AND CHARACTERISTIC OF CONTROL FOR TENSION SYSTEM WITH HIGH INERTIA LOADS

Based on the pressure regulation circuit adopting electro-hydraulic proportional relief valve to control tension, a new type of electro-hydraulic compound control circuit with throttle control unit is presented, which can obtain optimal dynamic damping ratio through real-time altering pressure-flow gain of the throttle control unit, improve the dynamic characteristic of tension follow-up control for the tension system with high inertia loads. Moreover, the characteristic when the cable linear velocity variation causes change of tension is investigated, and a compound control strategy is proposed. The theoretical analysis and experimental results show that the electro-hydraulic compound control circuit is effective and the characteristic of the compound control strategy is satisfactory.

Carrier Cells for Delivery of Oncolytic Measles Virus into Tumors：Determinants of Efficient Loading

Oncolytic measles virus(OMV) is a promising antitumor agent. However, the presence of anti-measles neutralizing antibodies(NAbs) against the hemagglutinin(H) protein of OMV is a major barrier to the therapeutic application of OMV in clinical practice. In order to overcome this challenge, specific types of cells have been used as carriers for OMV.Differential loading strategies appear to result in different therapeutic outcomes; despite this, only few studies have reported practical ex vivo loading strategies required for effective treatment. To this end, we systematically evaluated the antitumor efficacy of OMV using different loading strategies; this involved varying the in vitro loading duration and loading dose of OMV. We found that improved oncolysis of carrier cells was achieved by a prolonged loading duration in the absence of NAbs. However, the enhanced oncolytic effect was abrogated in the presence of NAbs. Further, we found that the expression of H protein on the surface of carrier cells was predominantly determined by the loading duration rather than the loading dose. Finally, we showed that NAbs blocked viral transfer by targeting H protein prior to the occurrence of cell-to-cell interactions. Our results provide comprehensive information on the determinants of an effective loading strategy for carrier cell-based virotherapy; these results may be useful for guiding the application of OMV as an antitumor agent in clinical practice.